# Statistical Inference for Partially Observed Markov Processes

## Documentation for package ‘pomp’ version 5.8

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Package NEWS.

## Help Pages

A B C D E F G H I K L M N O P R S T U V W

pomp-package | Inference for partially observed Markov processes

## -- A --

abc | Approximate Bayesian computation
abc-method | Approximate Bayesian computation
accumvars | accumulator variables

## -- B --

bake | Tools for reproducible computations
basic_components | Basic POMP model components.
basic_probes | Useful probes for partially-observed Markov processes
betabinomial | Beta-binomial distribution
blowflies | Nicholson's blowflies.
blowflies1 | Nicholson's blowflies.
blowflies2 | Nicholson's blowflies.
bsflu | Influenza outbreak in a boarding school
bsmc2 | The Liu and West Bayesian particle filter
bsmc2-method | The Liu and West Bayesian particle filter
bsplines | B-spline bases
bspline_basis | B-spline bases

## -- C --

c | Concatenate
c.Pomp | Concatenate
childhood_disease_data | Historical childhood disease incidence data
coef | Extract, set, or alter coefficients
coef-method | Extract, set, or alter coefficients
coef<- | Extract, set, or alter coefficients
coef<--method | Extract, set, or alter coefficients
compartmental_models | Compartmental epidemiological models
concat | Concatenate
cond_logLik | Conditional log likelihood
cond_logLik-method | Conditional log likelihood
continue | Continue an iterative calculation
continue-method | Continue an iterative calculation
covariates | Covariates
covariate_table | Covariates
covariate_table-method | Covariates
covmat | Estimate a covariance matrix from algorithm traces
covmat-method | Estimate a covariance matrix from algorithm traces
Csnippet | C snippets

## -- D --

dacca | Model of cholera transmission for historic Bengal.
dbetabinom | Beta-binomial distribution
design | Design matrices for pomp calculations
deulermultinom | Eulermultinomial and gamma-whitenoise distributions
dinit | dinit workhorse
dinit-method | dinit workhorse
dinit_spec | dinit specification
discrete_time | rprocess specification
dmeasure | dmeasure workhorse
dmeasure-method | dmeasure workhorse
dmeasure_spec | dmeasure specification
dprior | dprior workhorse
dprior-method | dprior workhorse
dprocess | dprocess workhorse
dprocess-method | dprocess workhorse
dprocess_spec | dprocess specification

## -- E --

eakf | Ensemble Kalman filters
eakf-method | Ensemble Kalman filters
ebola | Ebola outbreak, West Africa, 2014-2016
ebolaModel | Ebola outbreak, West Africa, 2014-2016
ebolaWA2014 | Ebola outbreak, West Africa, 2014-2016
eff_sample_size | Effective sample size
eff_sample_size-method | Effective sample size
elementary_algorithms | Elementary computations on POMP models.
emeasure | emeasure workhorse
emeasure-method | emeasure workhorse
emeasure_spec | emeasure specification
enkf | Ensemble Kalman filters
enkf-method | Ensemble Kalman filters
estimation_algorithms | Parameter estimation algorithms for POMP models.
euler | rprocess specification
eulermultinom | Eulermultinomial and gamma-whitenoise distributions
ewcitmeas | Historical childhood disease incidence data
ewmeas | Historical childhood disease incidence data
expit | Transformations

## -- F --

filter_mean | Filtering mean
filter_mean-method | Filtering mean
filter_traj | Filtering trajectories
filter_traj-method | Filtering trajectories
flow | flow workhorse
flow-method | flow workhorse
forecast | Forecast mean
forecast-method | Forecast mean
freeze | Tools for reproducible computations

## -- G --

gillespie | rprocess specification
gillespie_hl | rprocess specification
gompertz | Gompertz model with log-normal observations.

## -- H --

hitch | Hitching C snippets and R functions to pomp_fun objects

## -- I --

inv_log_barycentric | Transformations

## -- K --

kalman | Ensemble Kalman filters
kalmanFilter | Kalman filter

## -- L --

logit | Transformations
logLik | Log likelihood
logLik-method | Log likelihood
logmeanexp | The log-mean-exp trick
log_barycentric | Transformations
LondonYorke | Historical childhood disease incidence data
lookup | Lookup table

## -- M --

map | skeleton specification
mcap | Monte Carlo adjusted profile
melt | Melt
melt-method | Melt
mif2 | Iterated filtering: maximum likelihood by iterated, perturbed Bayes maps
mif2-method | Iterated filtering: maximum likelihood by iterated, perturbed Bayes maps
mvn_diag_rw | MCMC proposal distributions
mvn_rw | MCMC proposal distributions
mvn_rw_adaptive | MCMC proposal distributions

## -- N --

nlf | Nonlinear forecasting
nlf_objfun | Nonlinear forecasting
nlf_objfun-method | Nonlinear forecasting

## -- O --

obs | obs
obs-method | obs
onestep | rprocess specification
ou2 | Two-dimensional discrete-time Ornstein-Uhlenbeck process

## -- P --

parameter_trans | parameter transformations
parameter_trans-method | parameter transformations
parmat | Create a matrix of parameters
parmat-method | Create a matrix of parameters
partrans | partrans workhorse
partrans-method | partrans workhorse
parus | Parus major population dynamics
periodic_bspline_basis | B-spline bases
pfilter | Particle filter
pfilter-method | Particle filter
plot | pomp plotting facilities
plot-method | pomp plotting facilities
pmcmc | The particle Markov chain Metropolis-Hastings algorithm
pmcmc-method | The particle Markov chain Metropolis-Hastings algorithm
pomp | Constructor of the basic pomp object
pomp,package | Inference for partially observed Markov processes
pomp_constructor | Constructor of the basic pomp object
pomp_examples | pre-built pomp examples
pred_mean | Prediction mean
pred_mean-method | Prediction mean
pred_var | Prediction variance
pred_var-method | Prediction variance
priors | prior specification
prior_spec | prior specification
probe | Probes (AKA summary statistics)
probe-method | Probes (AKA summary statistics)
probe_acf | Useful probes for partially-observed Markov processes
probe_ccf | Useful probes for partially-observed Markov processes
probe_marginal | Useful probes for partially-observed Markov processes
probe_match | Probe matching
probe_mean | Useful probes for partially-observed Markov processes
probe_median | Useful probes for partially-observed Markov processes
probe_nlar | Useful probes for partially-observed Markov processes
probe_objfun | Probe matching
probe_objfun-method | Probe matching
probe_period | Useful probes for partially-observed Markov processes
probe_quantile | Useful probes for partially-observed Markov processes
probe_sd | Useful probes for partially-observed Markov processes
probe_var | Useful probes for partially-observed Markov processes
profile_design | Design matrices for pomp calculations
proposals | MCMC proposal distributions

## -- R --

rbetabinom | Beta-binomial distribution
reproducibility_tools | Tools for reproducible computations
reulermultinom | Eulermultinomial and gamma-whitenoise distributions
rgammawn | Eulermultinomial and gamma-whitenoise distributions
ricker | Ricker model with Poisson observations.
rinit | rinit workhorse
rinit-method | rinit workhorse
rinit_spec | rinit specification
rmeasure | rmeasure workhorse
rmeasure-method | rmeasure workhorse
rmeasure_spec | rmeasure specification
rprior | rprior workhorse
rprior-method | rprior workhorse
rprocess | rprocess workhorse
rprocess-method | rprocess workhorse
rprocess_spec | rprocess specification
runif_design | Design matrices for pomp calculations
rw2 | Two-dimensional random-walk process
rw_sd | rw_sd

## -- S --

sannbox | Simulated annealing with box constraints.
saved_states | Saved states
saved_states-method | Saved states
simulate | Simulations of a partially-observed Markov process
simulate-method | Simulations of a partially-observed Markov process
sir | Compartmental epidemiological models
sir2 | Compartmental epidemiological models
SIR_models | Compartmental epidemiological models
skeleton | skeleton workhorse
skeleton-method | skeleton workhorse
skeleton_spec | skeleton specification
slice_design | Design matrices for pomp calculations
sobol_design | Design matrices for pomp calculations
spect | Power spectrum
spect-method | Power spectrum
spect_match | Spectrum matching
spect_objfun | Spectrum matching
spect_objfun-method | Spectrum matching
spy | Spy
spy-method | Spy
states | Latent states
states-method | Latent states
stew | Tools for reproducible computations
summary | Summary methods
summary-method | Summary methods

## -- T --

time | Methods to extract and manipulate the obseration times
time-method | Methods to extract and manipulate the obseration times
time<- | Methods to extract and manipulate the obseration times
time<--method | Methods to extract and manipulate the obseration times
timezero | The zero time
timezero-method | The zero time
timezero<- | The zero time
timezero<--method | The zero time
traces | Traces
traces-method | Traces
trajectory | Trajectory of a deterministic model
trajectory-method | Trajectory of a deterministic model
traj_match | Trajectory matching
traj_objfun | Trajectory matching
traj_objfun-method | Trajectory matching
transformations | Transformations

## -- U --

userdata | Facilities for making additional information to basic components

## -- V --

vectorfield | skeleton specification
verhulst | Verhulst-Pearl model
vmeasure | vmeasure workhorse
vmeasure-method | vmeasure workhorse
vmeasure_spec | vmeasure specification

## -- W --

window | Window
window-method | Window
workhorses | Workhorse functions for the 'pomp' algorithms.
wpfilter | Weighted particle filter
wpfilter-method | Weighted particle filter
wquant | Weighted quantile function